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AI for Kids Worksheet: Part 1 Test

AI for students lesson 8: Part 1 test: what AI is · Set 734 · 40 questions
TalentJR

AI tip (Name the idea, then answer): Learning from examples → AI; fixed rules → a normal program. Order: training data → model → prediction; good data is many, varied and correctly labelled. Generative AI makes new things and can hallucinate; one-sided data causes bias.

NameDateTime takenScore ___ / 40
  1. 1.🔍 Which is the odd one out? (a) balance the data (b) add varied examples (c) use one group only (d) test on many groups
  2. 2.Which of these uses AI? (a) a stopwatch (b) a doorbell (c) a spam filter (d) a fan regulator
  3. 3.True or false: stories where every doctor is a man is one-sided data (likely to make a biased model). (a) True (b) False
  4. 4.🔢 An AI chatbot gives a sum’s answer. What is the smart thing to do? (a) check it on paper (b) never do maths (c) ask it to hurry (d) copy it straight away
  5. 5.🎨 An image generator makes a picture from… (a) a phone number (b) your password (c) the weather (d) a text description
  6. 6.🧪 Why test a model on NEW examples? (a) to make it slower (b) to see if it works (c) to change its name (d) to delete its data
  7. 7.🤖 Does an AI system think and feel like a person? (a) yes, it gets sad (b) no, it finds patterns (c) yes, just like us (d) only on weekends
  8. 8.Which of these describes how a normal program works? (a) spots patterns in data (b) improves with more data (c) gives a likely answer (d) never learns from data
  9. 9.True or false: recognising a friend’s face in photos only needs a simple fixed rule. (a) True (b) False
  10. 10.🔁 Training data, the model or a prediction: “old emails marked spam”? (a) training data (b) the model (c) a prediction
  11. 11.⚖️ One-sided or balanced data: leaves from every season of the year? (a) balanced data (b) one-sided data
  12. 12.⚖️ One-sided or balanced data: a leaf app trained only on summer leaves? (a) balanced data (b) one-sided data
  13. 13.✨ Generative or not: inventing a recipe? (a) makes something new (b) sorts or predicts
  14. 14.🛠️ Which does this job need: turning spoken words into typed text? (a) needs AI (learning) (b) a simple rule is enough
  15. 15.🔦 Is a torch with an on/off switch AI? (a) only if it is bright (b) no (c) yes
  16. 16.True or false: an image generator drawing a robot from a sentence is AI recognising something. (a) False (b) True
  17. 17.📱 What is the AI doing here: a keyboard guessing your next word? (a) recognising (b) recommending (c) generating (d) predicting
  18. 18.🛠️ Does this reduce bias or add to it: use one group only? (a) adds to bias (b) reduces bias
  19. 19.🤖 What does AI stand for? (a) actual information (b) app installer (c) artificial intelligence (d) automatic internet
  20. 20.🧐 Fact or myth: “AI knows everything”? (a) a myth (b) a fact
  21. 21.🥭 A model saw only ripe yellow mangoes. A raw green mango arrives. What may happen? (a) it will shut down (b) it will turn yellow (c) it may get it wrong (d) it will be perfect
  22. 22.🔍 Which is the odd one out? (a) ignore complaints (b) add varied examples (c) check who is missing (d) fix wrong labels
  23. 23.⌨️ Your phone keyboard suggests the next word. What is the AI doing? (a) singing (b) sleeping (c) drawing (d) predicting
  24. 24.🛠️ Does this reduce bias or add to it: test on many groups? (a) adds to bias (b) reduces bias
  25. 25.🔍 Which is the odd one out? (a) examples of every type (b) correct labels (c) wrong labels (d) checking labels twice
  26. 26.🛠️ What helps make an AI system fairer? (a) fewer tests (b) one group only (c) ignoring mistakes (d) more varied data
  27. 27.🔍 Which is the odd one out? (a) AI copies data patterns (b) AI is never wrong (c) AI can make up facts (d) AI answers need checking
  28. 28.Which of these is a fact about AI? (a) AI is never wrong (b) long answers are true (c) AI can be wrong (d) AI always checks facts
  29. 29.🔍 Which is the odd one out? (a) use one group only (b) skip testing (c) copy old unfair choices (d) balance the data
  30. 30.True or false: “new data for testing” is bad for training a model. (a) False (b) True
  31. 31.🔍 Which is the odd one out? (a) drafting a letter (b) sorting photos by face (c) inventing a recipe (d) drawing a new picture
  32. 32.Which of these is the model? (a) labelled fruit photos (b) tomorrow’s rain guess (c) old emails marked spam (d) the trained program
  33. 33.🎨 This prompt asks a generative AI for: a logo idea for the eco club. What kind of output is that? (a) text (b) an image (c) music or sound
  34. 34.🔍 Which is the odd one out? (a) reading number plates (b) creating a cartoon (c) making up a story (d) writing quiz questions
  35. 35.⏩ In machine learning, which comes first: the learned patterns or recorded spoken words? (a) the learned patterns (b) recorded spoken words
  36. 36.True or false: “match it to the textbook” is NOT a real way to check an AI answer. (a) False (b) True
  37. 37.🤖 AI or a normal program: which one “handles unseen examples”? (a) a normal program (b) AI
  38. 38.Which of these is generative AI (it makes something new)? (a) spotting spam (b) predicting rain (c) unlocking with a face (d) drawing a new picture
  39. 39.📱 What is the AI doing here: a book app suggesting a story like your last one? (a) predicting (b) recognising (c) generating (d) recommending
  40. 40.Which of these helps reduce bias? (a) test on one group only (b) add varied examples (c) copy old unfair choices (d) skip testing

Answer key

  1. use one group only
  2. a spam filter
  3. True
  4. check it on paper
  5. a text description
  6. to see if it works
  7. no, it finds patterns
  8. never learns from data
  9. False
  10. training data
  11. balanced data
  12. one-sided data
  13. makes something new
  14. needs AI (learning)
  15. no
  16. False
  17. predicting
  18. adds to bias
  19. artificial intelligence
  20. a myth
  21. it may get it wrong
  22. ignore complaints
  23. predicting
  24. reduces bias
  25. wrong labels
  26. more varied data
  27. AI is never wrong
  28. AI can be wrong
  29. balance the data
  30. False
  31. sorting photos by face
  32. the trained program
  33. an image
  34. reading number plates
  35. recorded spoken words
  36. False
  37. AI
  38. drawing a new picture
  39. recommending
  40. add varied examples

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